Author

Houde Liu

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Preprint Jul 2026

ST-WAM: Semantic-Temporal World Action Model for Robust Manipulation under Visual Distribution Shifts

Semantic-Temporal WAM (ST-WAM) is proposed to improve action robustness by using DINOv3 as a shared semantic representation for future prediction and history retrieval while retaining fine-grained VAE dynamics, demonstrating that semantic-temporal modeling effectively complements pixel-generative dynamics for robust manipulation.

Mingxin Wang, Bin Hu, Bin Qian et al. · 1 citation

Jun 2026

Stage-Transition Dense Reward Modeling for Reinforcement Learning

Experiments show that STDR consistently improves sample efficiency and success rates over multiple baselines, and matches or surpasses handcrafted dense rewards on several challenging tasks, suggesting robustness to visual noise and better-calibrated reward assignment across settings.

Yang Yang, Bingjie Chen, Zihan Wang et al. · arXiv.org · 0 citations